Replacing zero values in dataframe using another dataframe

Question

I would like to replace some of the values in the foll. dataframe:

dataframe_a

Y2000   Y2001   Y2002    Y2003    Y2004    Item    Item Code
34        43      0      0          25     Test      Val

I would like to replace the values in the columns with a numeric value derived by multiplying a scalar (say 0.5) by all values in this dataframe:

dataframe_b

Y2000   Y2001   Y2002    Y2003    Y2004    Item    Item Code
34        43      10      20        25     Test      Val

So, in dataframe_a value for column Y2002 should be 10 * 0.5 and value for column Y2003 should be 20 * 0.5

Currently, I am doing this:

df = dataframe_a[dataframe_a == 0]
df = df * dataframe_b * 0.5

However, not sure how I can update dataframe_a with the new values

Answer 1

You can use the boolean mask and then call fillna:

In [58]:
fill = df2.select_dtypes(include = [np.number]) * 0.5
df1 = df1[df1!=0].fillna(fill)
df1

Out[58]:
   Y2000  Y2001  Y2002  Y2003  Y2004  Item Item  Code
0     34     43      5     10     25  Test        Val

Here df1[df1 !=0] will produce a df of the same shape with NaN values where the condition is not met, you can then call fillna on this and pass the other df which will replace the NaN values where the index and columns align.

The result of the boolean mask:

In [63]:
df1[df1!=0]

Out[63]:
   Y2000  Y2001  Y2002  Y2003  Y2004  Item Item  Code
0     34     43    NaN    NaN     25  Test        Val